Article thumbnail

Error Detection in Panoramic Videos: a Pairwise Assessment within Stitching

By Sandra Nabil, Frédéric Devernay and James L. Crowley

Abstract

One way to provide realistic immersive VR content relies on producing high-quality panoramic videos. These videos are usually produced using multiple cameras with different optical centers and which may not be perfectly synchronized This results in spatial and temporal artifact, even though the blending algorithm strives to reduce them. In this paper, we devise a method that detects potential visual artifacts, based on existing view synthesis quality metrics. The method works by computing pair-wise quality at each blending step and fusing them to produce a global map of potential errors. To get a more accurate prediction, we develop a mask that is then applied to the error map and therefore accentuates the defects on the blending cutting line. Results show that the calculated distortion map succeeds to identify visual artifacts in panoramas which can help design better solutions to this problem in the future

Topics: parallax error, panoramic videos, image blending, quality metrics, error prediction, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Publisher: HAL CCSD
Year: 2017
OAI identifier: oai:HAL:hal-01849267v1
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • https://hal.archives-ouvertes.... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.